{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 上市公司营收预测实战分析"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 一、案例介绍\n",
    "在金融领域，上市公司营收预测是非常重要的，因为它直接反映了公司的运营情况和未来发展趋势。投资者和金融数据分析师通常会关注上市公司营收预测，以评估上市公司的业绩表现和投资潜力。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 二、实现目标\n",
    "- 建立上市公司营收预测模型\n",
    "- 评价模型的性能\n",
    "- 探索影响上市公司营收的关键因素"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 三、实战任务"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 导入必要的库\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "# 设置中文显示\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "读取数据...\n",
      "数据加载完成\n",
      "数据形状: (4996, 12)\n",
      "\n",
      "数据前5行:\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>证券代码</th>\n",
       "      <th>证券简称</th>\n",
       "      <th>营业收入</th>\n",
       "      <th>营业成本</th>\n",
       "      <th>资产总计</th>\n",
       "      <th>负债合计</th>\n",
       "      <th>归属于母公司所有者权益合计</th>\n",
       "      <th>所有者权益合计</th>\n",
       "      <th>经营活动产生的现金流量净额</th>\n",
       "      <th>投资活动产生的现金流量净额</th>\n",
       "      <th>筹资活动产生的现金流量净额</th>\n",
       "      <th>现金及现金等价物净增加额</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>600004.SSE</td>\n",
       "      <td>白云机场</td>\n",
       "      <td>4.607372e+09</td>\n",
       "      <td>3.672784e+09</td>\n",
       "      <td>2.676530e+10</td>\n",
       "      <td>9.079184e+09</td>\n",
       "      <td>1.746457e+10</td>\n",
       "      <td>1.768612e+10</td>\n",
       "      <td>1.899870e+09</td>\n",
       "      <td>-4.484768e+08</td>\n",
       "      <td>-1.241910e+09</td>\n",
       "      <td>2.094994e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>600006.SSE</td>\n",
       "      <td>东风汽车</td>\n",
       "      <td>9.167268e+09</td>\n",
       "      <td>8.742790e+09</td>\n",
       "      <td>1.849137e+10</td>\n",
       "      <td>1.005371e+10</td>\n",
       "      <td>8.147862e+09</td>\n",
       "      <td>8.437663e+09</td>\n",
       "      <td>-4.134473e+08</td>\n",
       "      <td>7.154362e+07</td>\n",
       "      <td>-2.028714e+08</td>\n",
       "      <td>-5.419016e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>600007.SSE</td>\n",
       "      <td>中国国贸</td>\n",
       "      <td>3.953762e+09</td>\n",
       "      <td>1.660074e+09</td>\n",
       "      <td>1.288114e+10</td>\n",
       "      <td>3.177151e+09</td>\n",
       "      <td>9.700158e+09</td>\n",
       "      <td>9.703984e+09</td>\n",
       "      <td>1.918661e+09</td>\n",
       "      <td>-6.483579e+07</td>\n",
       "      <td>-1.289834e+09</td>\n",
       "      <td>5.636168e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>600008.SSE</td>\n",
       "      <td>首创环保</td>\n",
       "      <td>1.413120e+10</td>\n",
       "      <td>9.294286e+09</td>\n",
       "      <td>1.072722e+11</td>\n",
       "      <td>6.701086e+10</td>\n",
       "      <td>2.901710e+10</td>\n",
       "      <td>4.026134e+10</td>\n",
       "      <td>1.948576e+09</td>\n",
       "      <td>-3.922369e+09</td>\n",
       "      <td>1.071122e+09</td>\n",
       "      <td>-8.975556e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>600009.SSE</td>\n",
       "      <td>上海机场</td>\n",
       "      <td>1.104702e+10</td>\n",
       "      <td>9.222978e+09</td>\n",
       "      <td>6.948053e+10</td>\n",
       "      <td>2.745396e+10</td>\n",
       "      <td>4.054165e+10</td>\n",
       "      <td>4.202657e+10</td>\n",
       "      <td>4.020086e+09</td>\n",
       "      <td>-2.641219e+09</td>\n",
       "      <td>-6.377018e+08</td>\n",
       "      <td>7.387446e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         证券代码  证券简称          营业收入          营业成本          资产总计          负债合计  \\\n",
       "0  600004.SSE  白云机场  4.607372e+09  3.672784e+09  2.676530e+10  9.079184e+09   \n",
       "1  600006.SSE  东风汽车  9.167268e+09  8.742790e+09  1.849137e+10  1.005371e+10   \n",
       "2  600007.SSE  中国国贸  3.953762e+09  1.660074e+09  1.288114e+10  3.177151e+09   \n",
       "3  600008.SSE  首创环保  1.413120e+10  9.294286e+09  1.072722e+11  6.701086e+10   \n",
       "4  600009.SSE  上海机场  1.104702e+10  9.222978e+09  6.948053e+10  2.745396e+10   \n",
       "\n",
       "   归属于母公司所有者权益合计       所有者权益合计  经营活动产生的现金流量净额  投资活动产生的现金流量净额  筹资活动产生的现金流量净额  \\\n",
       "0   1.746457e+10  1.768612e+10   1.899870e+09  -4.484768e+08  -1.241910e+09   \n",
       "1   8.147862e+09  8.437663e+09  -4.134473e+08   7.154362e+07  -2.028714e+08   \n",
       "2   9.700158e+09  9.703984e+09   1.918661e+09  -6.483579e+07  -1.289834e+09   \n",
       "3   2.901710e+10  4.026134e+10   1.948576e+09  -3.922369e+09   1.071122e+09   \n",
       "4   4.054165e+10  4.202657e+10   4.020086e+09  -2.641219e+09  -6.377018e+08   \n",
       "\n",
       "   现金及现金等价物净增加额  \n",
       "0  2.094994e+08  \n",
       "1 -5.419016e+08  \n",
       "2  5.636168e+08  \n",
       "3 -8.975556e+08  \n",
       "4  7.387446e+08  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 1. 设计指标，收集与整理数据\n",
    "print('读取数据...')\n",
    "# 读取数据文件（使用绝对路径）\n",
    "file_path = r'c:\\Users\\YEDX\\FinancialAnalysis\\chapter5\\上市公司营收数据.xlsx'\n",
    "df = pd.read_excel(file_path)\n",
    "\n",
    "print('数据加载完成')\n",
    "print(f'数据形状: {df.shape}')\n",
    "print('\\n数据前5行:')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "数据信息:\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4996 entries, 0 to 4995\n",
      "Data columns (total 12 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   证券代码           4996 non-null   object \n",
      " 1   证券简称           4996 non-null   object \n",
      " 2   营业收入           4996 non-null   float64\n",
      " 3   营业成本           4996 non-null   float64\n",
      " 4   资产总计           4996 non-null   float64\n",
      " 5   负债合计           4996 non-null   float64\n",
      " 6   归属于母公司所有者权益合计  4996 non-null   float64\n",
      " 7   所有者权益合计        4996 non-null   float64\n",
      " 8   经营活动产生的现金流量净额  4996 non-null   float64\n",
      " 9   投资活动产生的现金流量净额  4996 non-null   float64\n",
      " 10  筹资活动产生的现金流量净额  4996 non-null   float64\n",
      " 11  现金及现金等价物净增加额   4996 non-null   float64\n",
      "dtypes: float64(10), object(2)\n",
      "memory usage: 468.5+ KB\n",
      "\n",
      "数据描述性统计:\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>营业收入</th>\n",
       "      <th>营业成本</th>\n",
       "      <th>资产总计</th>\n",
       "      <th>负债合计</th>\n",
       "      <th>归属于母公司所有者权益合计</th>\n",
       "      <th>所有者权益合计</th>\n",
       "      <th>经营活动产生的现金流量净额</th>\n",
       "      <th>投资活动产生的现金流量净额</th>\n",
       "      <th>筹资活动产生的现金流量净额</th>\n",
       "      <th>现金及现金等价物净增加额</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>4.996000e+03</td>\n",
       "      <td>4.996000e+03</td>\n",
       "      <td>4.996000e+03</td>\n",
       "      <td>4.996000e+03</td>\n",
       "      <td>4.996000e+03</td>\n",
       "      <td>4.996000e+03</td>\n",
       "      <td>4.996000e+03</td>\n",
       "      <td>4.996000e+03</td>\n",
       "      <td>4.996000e+03</td>\n",
       "      <td>4.996000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.099438e+10</td>\n",
       "      <td>9.033468e+09</td>\n",
       "      <td>2.099598e+10</td>\n",
       "      <td>1.227536e+10</td>\n",
       "      <td>7.504878e+09</td>\n",
       "      <td>8.720620e+09</td>\n",
       "      <td>1.012196e+09</td>\n",
       "      <td>-9.321143e+08</td>\n",
       "      <td>-7.794590e+07</td>\n",
       "      <td>8.829482e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>8.090548e+10</td>\n",
       "      <td>6.753510e+10</td>\n",
       "      <td>1.058781e+11</td>\n",
       "      <td>6.916695e+10</td>\n",
       "      <td>3.708692e+10</td>\n",
       "      <td>4.324788e+10</td>\n",
       "      <td>1.008246e+10</td>\n",
       "      <td>6.781709e+09</td>\n",
       "      <td>4.587373e+09</td>\n",
       "      <td>2.895905e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.391344e+05</td>\n",
       "      <td>1.010566e+05</td>\n",
       "      <td>1.117365e+08</td>\n",
       "      <td>8.440723e+06</td>\n",
       "      <td>-1.012120e+10</td>\n",
       "      <td>-1.308377e+10</td>\n",
       "      <td>-8.236324e+10</td>\n",
       "      <td>-2.557890e+11</td>\n",
       "      <td>-1.465720e+11</td>\n",
       "      <td>-9.119754e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>5.656242e+08</td>\n",
       "      <td>3.643836e+08</td>\n",
       "      <td>1.967421e+09</td>\n",
       "      <td>5.236481e+08</td>\n",
       "      <td>1.211943e+09</td>\n",
       "      <td>1.244421e+09</td>\n",
       "      <td>-2.483174e+07</td>\n",
       "      <td>-4.405557e+08</td>\n",
       "      <td>-1.437665e+08</td>\n",
       "      <td>-1.774267e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.439621e+09</td>\n",
       "      <td>9.988800e+08</td>\n",
       "      <td>3.883674e+09</td>\n",
       "      <td>1.446936e+09</td>\n",
       "      <td>2.225151e+09</td>\n",
       "      <td>2.311165e+09</td>\n",
       "      <td>8.674738e+07</td>\n",
       "      <td>-1.313464e+08</td>\n",
       "      <td>-1.502629e+07</td>\n",
       "      <td>-2.250101e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>4.215207e+09</td>\n",
       "      <td>3.130592e+09</td>\n",
       "      <td>1.008897e+10</td>\n",
       "      <td>4.766490e+09</td>\n",
       "      <td>5.043774e+09</td>\n",
       "      <td>5.291062e+09</td>\n",
       "      <td>3.785356e+08</td>\n",
       "      <td>-1.514302e+07</td>\n",
       "      <td>1.667204e+08</td>\n",
       "      <td>1.408973e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>3.212215e+12</td>\n",
       "      <td>2.709656e+12</td>\n",
       "      <td>2.852437e+12</td>\n",
       "      <td>2.133019e+12</td>\n",
       "      <td>1.446410e+12</td>\n",
       "      <td>1.630621e+12</td>\n",
       "      <td>4.565960e+11</td>\n",
       "      <td>6.242676e+09</td>\n",
       "      <td>1.006234e+11</td>\n",
       "      <td>8.053617e+10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               营业收入          营业成本          资产总计          负债合计  归属于母公司所有者权益合计  \\\n",
       "count  4.996000e+03  4.996000e+03  4.996000e+03  4.996000e+03   4.996000e+03   \n",
       "mean   1.099438e+10  9.033468e+09  2.099598e+10  1.227536e+10   7.504878e+09   \n",
       "std    8.090548e+10  6.753510e+10  1.058781e+11  6.916695e+10   3.708692e+10   \n",
       "min    1.391344e+05  1.010566e+05  1.117365e+08  8.440723e+06  -1.012120e+10   \n",
       "25%    5.656242e+08  3.643836e+08  1.967421e+09  5.236481e+08   1.211943e+09   \n",
       "50%    1.439621e+09  9.988800e+08  3.883674e+09  1.446936e+09   2.225151e+09   \n",
       "75%    4.215207e+09  3.130592e+09  1.008897e+10  4.766490e+09   5.043774e+09   \n",
       "max    3.212215e+12  2.709656e+12  2.852437e+12  2.133019e+12   1.446410e+12   \n",
       "\n",
       "            所有者权益合计  经营活动产生的现金流量净额  投资活动产生的现金流量净额  筹资活动产生的现金流量净额  现金及现金等价物净增加额  \n",
       "count  4.996000e+03   4.996000e+03   4.996000e+03   4.996000e+03  4.996000e+03  \n",
       "mean   8.720620e+09   1.012196e+09  -9.321143e+08  -7.794590e+07  8.829482e+06  \n",
       "std    4.324788e+10   1.008246e+10   6.781709e+09   4.587373e+09  2.895905e+09  \n",
       "min   -1.308377e+10  -8.236324e+10  -2.557890e+11  -1.465720e+11 -9.119754e+10  \n",
       "25%    1.244421e+09  -2.483174e+07  -4.405557e+08  -1.437665e+08 -1.774267e+08  \n",
       "50%    2.311165e+09   8.674738e+07  -1.313464e+08  -1.502629e+07 -2.250101e+07  \n",
       "75%    5.291062e+09   3.785356e+08  -1.514302e+07   1.667204e+08  1.408973e+08  \n",
       "max    1.630621e+12   4.565960e+11   6.242676e+09   1.006234e+11  8.053617e+10  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看数据信息\n",
    "print('数据信息:')\n",
    "df.info()\n",
    "\n",
    "print('\\n数据描述性统计:')\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "缺失值情况:\n",
      "证券代码             0\n",
      "证券简称             0\n",
      "营业收入             0\n",
      "营业成本             0\n",
      "资产总计             0\n",
      "负债合计             0\n",
      "归属于母公司所有者权益合计    0\n",
      "所有者权益合计          0\n",
      "经营活动产生的现金流量净额    0\n",
      "投资活动产生的现金流量净额    0\n",
      "筹资活动产生的现金流量净额    0\n",
      "现金及现金等价物净增加额     0\n",
      "dtype: int64\n",
      "\n",
      "处理后缺失值情况:\n",
      "证券代码             0\n",
      "证券简称             0\n",
      "营业收入             0\n",
      "营业成本             0\n",
      "资产总计             0\n",
      "负债合计             0\n",
      "归属于母公司所有者权益合计    0\n",
      "所有者权益合计          0\n",
      "经营活动产生的现金流量净额    0\n",
      "投资活动产生的现金流量净额    0\n",
      "筹资活动产生的现金流量净额    0\n",
      "现金及现金等价物净增加额     0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# 数据预处理\n",
    "print('\\n缺失值情况:')\n",
    "print(df.isnull().sum())\n",
    "\n",
    "# 处理缺失值\n",
    "numeric_cols = df.select_dtypes(include=[np.number]).columns\n",
    "df[numeric_cols] = df[numeric_cols].fillna(df[numeric_cols].mean())\n",
    "\n",
    "# 检查是否还有缺失值\n",
    "print('\\n处理后缺失值情况:')\n",
    "print(df.isnull().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 特征工程\n",
    "# 添加可能有用的特征\n",
    "if '年份' in df.columns:\n",
    "    df['年份_sqrt'] = np.sqrt(df['年份'])\n",
    "\n",
    "# 特征相关性分析\n",
    "numeric_cols = df.select_dtypes(include=[np.number]).columns\n",
    "if len(numeric_cols) > 0:\n",
    "    plt.figure(figsize=(12, 10))\n",
    "    corr = df[numeric_cols].corr()\n",
    "    sns.heatmap(corr, annot=True, cmap='coolwarm', fmt='.2f')\n",
    "    plt.title('特征相关性热力图')\n",
    "    plt.tight_layout()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "目标变量: 营业收入\n",
      "\n",
      "特征数量: 9\n",
      "特征列表: ['营业成本', '资产总计', '负债合计', '归属于母公司所有者权益合计', '所有者权益合计', '经营活动产生的现金流量净额', '投资活动产生的现金流量净额', '筹资活动产生的现金流量净额', '现金及现金等价物净增加额']\n"
     ]
    }
   ],
   "source": [
    "# 准备特征和目标变量\n",
    "# 自动查找目标变量（包含'营收'或'收入'的列）\n",
    "target_col = None\n",
    "for col in df.columns:\n",
    "    if '营收' in col or '收入' in col:\n",
    "        target_col = col\n",
    "        break\n",
    "\n",
    "if target_col is None:\n",
    "    # 如果找不到明确的营收列，使用数值列的最后一列\n",
    "    numeric_cols = df.select_dtypes(include=[np.number]).columns\n",
    "    if len(numeric_cols) > 1:\n",
    "        target_col = numeric_cols[-1]\n",
    "        print(f'\\n未找到明确的营收列，使用 {target_col} 作为目标变量')\n",
    "    else:\n",
    "        raise ValueError('无法确定目标变量')\n",
    "\n",
    "print(f'\\n目标变量: {target_col}')\n",
    "\n",
    "# 选择特征（排除目标变量和非数值型特征）\n",
    "X = df.select_dtypes(include=[np.number]).drop(target_col, axis=1, errors='ignore')\n",
    "y = df[target_col]\n",
    "\n",
    "# 确保特征数量足够\n",
    "if X.shape[1] == 0:\n",
    "    print('\\n警告：未找到有效特征！尝试添加一些简单特征...')\n",
    "    # 创建一些基本特征\n",
    "    X = pd.DataFrame()\n",
    "    X['样本索引'] = np.arange(len(df))\n",
    "    if '年份' in df.columns:\n",
    "        X['年份'] = df['年份']\n",
    "\n",
    "print(f'\\n特征数量: {X.shape[1]}')\n",
    "print(f'特征列表: {list(X.columns)}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. 建立两种模型预测上市公司营收"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 划分训练集和测试集\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "# 标准化\n",
    "scaler = StandardScaler()\n",
    "X_train_scaled = scaler.fit_transform(X_train)\n",
    "X_test_scaled = scaler.transform(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "线性回归模型:\n",
      "均方误差 (MSE): 31923195067107647488.0000\n",
      "R² 评分: 0.9973\n"
     ]
    }
   ],
   "source": [
    "# 模型1：线性回归\n",
    "lr_model = LinearRegression()\n",
    "lr_model.fit(X_train_scaled, y_train)\n",
    "lr_pred = lr_model.predict(X_test_scaled)\n",
    "lr_mse = mean_squared_error(y_test, lr_pred)\n",
    "lr_r2 = r2_score(y_test, lr_pred)\n",
    "\n",
    "print('\\n线性回归模型:')\n",
    "print(f'均方误差 (MSE): {lr_mse:.4f}')\n",
    "print(f'R² 评分: {lr_r2:.4f}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "随机森林回归模型:\n",
      "均方误差 (MSE): 415172715973974491136.0000\n",
      "R² 评分: 0.9643\n"
     ]
    }
   ],
   "source": [
    "# 模型2：随机森林回归\n",
    "rf_model = RandomForestRegressor(n_estimators=100, random_state=42)\n",
    "rf_model.fit(X_train, y_train)\n",
    "rf_pred = rf_model.predict(X_test)\n",
    "rf_mse = mean_squared_error(y_test, rf_pred)\n",
    "rf_r2 = r2_score(y_test, rf_pred)\n",
    "\n",
    "print('\\n随机森林回归模型:')\n",
    "print(f'均方误差 (MSE): {rf_mse:.4f}')\n",
    "print(f'R² 评分: {rf_r2:.4f}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. 确定最终的预测模型，评价模型性能"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "模型对比:\n",
      "线性回归 R²: 0.9973\n",
      "随机森林 R²: 0.9643\n",
      "\n",
      "最佳模型: 线性回归\n",
      "最佳R²评分: 0.9973\n"
     ]
    }
   ],
   "source": [
    "# 确定最佳模型\n",
    "best_model = rf_model if rf_r2 > lr_r2 else lr_model\n",
    "best_model_name = \"随机森林\" if rf_r2 > lr_r2 else \"线性回归\"\n",
    "best_r2 = max(rf_r2, lr_r2)\n",
    "\n",
    "print('\\n模型对比:')\n",
    "print(f'线性回归 R²: {lr_r2:.4f}')\n",
    "print(f'随机森林 R²: {rf_r2:.4f}')\n",
    "print(f'\\n最佳模型: {best_model_name}')\n",
    "print(f'最佳R²评分: {best_r2:.4f}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. 探索影响上市公司营收的关键因素"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "特征重要性（前10个）:\n",
      "         feature  importance\n",
      "0           营业成本    0.649941\n",
      "1           资产总计    0.177986\n",
      "6  投资活动产生的现金流量净额    0.062286\n",
      "4        所有者权益合计    0.046958\n",
      "8   现金及现金等价物净增加额    0.023667\n",
      "2           负债合计    0.016628\n",
      "3  归属于母公司所有者权益合计    0.013748\n",
      "5  经营活动产生的现金流量净额    0.004672\n",
      "7  筹资活动产生的现金流量净额    0.004114\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 特征重要性分析（随机森林）\n",
    "feature_importance = pd.DataFrame({\n",
    "    'feature': X.columns,\n",
    "    'importance': rf_model.feature_importances_\n",
    "}).sort_values('importance', ascending=False)\n",
    "\n",
    "print('\\n特征重要性（前10个）:')\n",
    "print(feature_importance.head(10))\n",
    "\n",
    "# 可视化特征重要性\n",
    "plt.figure(figsize=(12, 8))\n",
    "# 确保有足够的数据进行可视化\n",
    "plot_data = feature_importance.head(min(10, len(feature_importance)))\n",
    "sns.barplot(x='importance', y='feature', data=plot_data)\n",
    "plt.title('特征重要性分析（随机森林）')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 可视化预测结果\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.scatter(y_test, lr_pred, alpha=0.5, label='线性回归')\n",
    "plt.scatter(y_test, rf_pred, alpha=0.5, label='随机森林')\n",
    "plt.plot([y_test.min(), y_test.max()], [y_test.min(), y_test.max()], 'k--', lw=2)\n",
    "plt.xlabel('实际营收')\n",
    "plt.ylabel('预测营收')\n",
    "plt.title('预测结果对比')\n",
    "plt.legend()\n",
    "plt.grid(True, alpha=0.3)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 四、总结与结论"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "===== 上市公司营收预测分析结论 =====\n",
      "1. 最佳预测模型: 线性回归\n",
      "2. 模型性能(R²): 0.9973\n",
      "3. 影响营收的关键因素(前5个):\n",
      "   - 营业成本: 0.6499\n",
      "   - 资产总计: 0.1780\n",
      "   - 投资活动产生的现金流量净额: 0.0623\n",
      "   - 所有者权益合计: 0.0470\n",
      "   - 现金及现金等价物净增加额: 0.0237\n",
      "\n",
      "4. 结论与建议:\n",
      "   - 线性回归模型在本次营收预测任务中表现最佳\n",
      "   - 根据特征重要性分析，应重点关注前几个关键因素进行营收预测和分析\n",
      "   - 建议定期更新模型，以适应市场变化\n",
      "   - 可考虑引入更多外部因素（如宏观经济指标、行业数据等）提高预测准确性\n"
     ]
    }
   ],
   "source": [
    "# 生成最终结论\n",
    "print('\\n===== 上市公司营收预测分析结论 =====')\n",
    "print(f'1. 最佳预测模型: {best_model_name}')\n",
    "print(f'2. 模型性能(R²): {best_r2:.4f}')\n",
    "print('3. 影响营收的关键因素(前5个):')\n",
    "for i, row in feature_importance.head(5).iterrows():\n",
    "    print(f'   - {row[\"feature\"]}: {row[\"importance\"]:.4f}')\n",
    "print('\\n4. 结论与建议:')\n",
    "print(f'   - {best_model_name}模型在本次营收预测任务中表现最佳')\n",
    "print('   - 根据特征重要性分析，应重点关注前几个关键因素进行营收预测和分析')\n",
    "print('   - 建议定期更新模型，以适应市场变化')\n",
    "print('   - 可考虑引入更多外部因素（如宏观经济指标、行业数据等）提高预测准确性')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
